mamma mia readme.md

README.md

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+# FEEL-IT: Emotion and Sentiment Classification for the Italian Language
+## Abstract
+
+Sentiment analysis is a common task to understand people's reactions online. Still, we often need more nuanced information: is the post negative because the user is angry or because they are sad?
+An abundance of approaches has been introduced for tackling both tasks. However, at least for Italian, they all treat only one of the tasks at a time. We introduce FEEL-IT, a novel benchmark corpus of Italian Twitter posts annotated with four basic emotions: anger, fear, joy, sadness. By collapsing them, we can also do sentiment analysis. We evaluate our corpus on benchmark datasets for both emotion and sentiment classification, obtaining competitive results.
+We release an open-source Python library, so researchers can use a model trained on FEEL-IT for inferring both sentiments and emotions from Italian text.
+
+| Model | Download |
+| ------ | ------ |
+| `feel-it-italian-sentiment` | [Link](https://huggingface.co/MilaNLProc/feel-it-italian-sentiment) |
+| `feel-it-italian-emotion` | Soon |